How does Neurala secure images and videos?
Images are stored with Amazon S3 security (HTTPS Protocols) with timed expiration URLs
By default, data is currently not encrypted at rest.
What browsers and devices does Brain Builder support?
Can Brain Builder be installed on-premise?
How does AI Video Annotation work?
How is Brain Builder updated? Is that part of the contract?
How does a customer add a new class to an existing brain or improve its performance with more data?
One of the many benefits of our L-DNN technology is that it supports this use model quite well. Users just need to log into the dataset that contains the brain and add the new class and supporting images. While training the new class, Published brains will have no impact. Once the user is satisfied with the performance of the current brain, it can get promoted to staging or Production for use in the field. The training process is almost immediate so adding classes or improving performance is easily done.
How do we receive predictions and integrate into our solution?
You can access all your custom brains via an HTTP API. You can also download an iOS, Android or Linux SDK, and integrate that to your application via an Objective-C, Java, or C++API, respectively. The downloadable SDK has the ability to download an updated brain from Brain Builder, and also to add knowledge (new examples or classes) to the brain locally.
Data In & Data Out
What types of Images and Videos does Brain Builder support?
What formats of data exports are supported?
Annotations can be exported in formats for TensorFlow and Caffe.
Brain Builder also supports exports in JSON, which can be easily converted to other formats and configurations.
What about other exports, like LMDB, HDF5, TFRecords, YOLO, etc.
Brain Builder does not currently support these export formats. After consulting with researchers, there are enough variables in how this is set up that it makes sense for the Brain Builder user to take care of this themselves.
The Brain Builder JSON export can be easily converted to other formats with some light scripting work.
Can Brain Builder export videos?
Brain Builder exports annotated video frames as individual images. We’ve seen very few clients use videos to train networks, as there are even more video formats, codecs, etc to support than image types. Supporting video formats, therefore, adds a layer of complexity to the training process, or failure point. Training on videos is not standard.
How does the data export process work?
Can you send me a copy of all of my uploaded data?
Why would you want a color-coded mask vs. a mask for each class per image (black & white)
What is the difference between Training, Validation, and Test data?
Once I’ve downloaded the dataset, are formats 100% ready to be uploaded into Tensor Flow and CAFFE? What’s the next step?
Does the system cope well with unbalanced classes?
This really depends on the dataset, but in general, balanced is typically better.
What are the deployment options?
How fast will Cloud inference be?
Can this run without connection to the internet?
What are the minimum hardware requirements for a recognition use case?
iOS: iOS 11.0 or later
Android: 8.1 (API level 27) or higher (where Android NNAPI is available)
Linux: Ubuntu 16.04, 4+ Core 1+GHz ARM or Intel 64-bit CPU, 200+MB RAM, (CUDA 9.0+)
What are the different frame rates for sample hardware in recognition use cases?
Does an API call that bundles several images into a single call consume a single API Inference or are the Inferences counted per image?
Each image constitutes an Inference Call and counts towards your overall account limit.
Why can't I promote my Brain?
If the Promote button is disabled, it means no additional training has been done since the last time you deployed, and therefore, it is the same Brain. If you wish to retrain your Brain, click Optimize or Retrain button to potentially adjust your Brain score.
What are the features and functionality available to different user roles?
What is the support model?
Does Neurala offer consulting services?
Technical (Nerds Only)
What features does L-DNN Recognition work well for (i.e. how do I understand what use case is a good one for L-DNN)?
The more distinct the features of different classes are, the better L-DNN (or DNN) will perform in prediction accuracy. Conversely, the more similar the inputs across classes, the higher the error rate.
What is the base size of L-DNN Recognition, especially as I consider running it on the Edge? Will I be able to see how the size is affected as I add new training data? How much memory do I need to keep free on my processor?
Other DNN Roadmap
What other neural network architectures will Brain Builder offer?
After I upload my imagery into Brain Builder, how is it modified? How is it modified for processing/inference by L-DNN? When I run inference on the L-DNN are there size inputs I can adjust for? What is the maximum? What is the minimum? How does that impact processing time?
At rest, access is limited to specific servers through IAM roles. Engineers can access assets at rest with secret keys.
In transit, all transfers use SSL (HTTPS).
The database gets backed up every day.
Employee Security Policy
Only employees with Administrator accounts on AWS can access customer assets.
Only needed employees can access our production database.
All employee keys and accounts are revoked at the time of termination.
Have a question you don't see here? Email firstname.lastname@example.org and our team will be happy to answer!
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